SOURCE: A registry-based prediction model for overall survival in patients with metastatic oesophageal or gastric cancer

H. ctor G. van den Boorn, Ameen Abu-Hanna, Emil ter Veer, Jessy Joy van Kleef, Florian Lordick, Michael Stahl, Jaffer A. Ajani, Rosine Guimbaud, Se Hoon Park, Susan J. Dutton, Yung-Jue Bang, Narikazu Boku, Nadia Haj Mohammad, Mirjam A. G. Sprangers, Rob H. A. Verhoeven, Aeilko H. Zwinderman, Martijn G. H. van Oijen, Hanneke W. M. van Laarhoven

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

�Prediction models are only sparsely available for metastatic oesophagogastric cancer. Because treatment in this setting is often preference-based, decision-making with the aid of a prediction model is wanted. The aim of this study is to construct a prediction model, called SOURCE, for the overall survival in patients with metastatic oesophagogastric cancer. Data from patients with metastatic oesophageal (n = 8010) or gastric (n = 4763) cancer diagnosed during 2005– 2015 were retrieved from the nationwide Netherlands cancer registry. A multivariate Cox regression model was created to predict overall survival for various treatments. Predictor selection was performed via the Akaike Information Criterion and a Delphi consensus among experts in palliative oesophagogastric cancer. Validation was performed according to a temporal internal-external scheme. The predictive quality was assessed with the concordance-index (c-index) and calibration. The model c-indices showed consistent discriminative ability during validation: 0.71 for oesophageal cancer and 0.68 for gastric cancer. The calibration showed an average slope of 1.0 and intercept of 0.0 for both tumour locations, indicating a close agreement between predicted and observed survival. With a fair c-index and good calibration, SOURCE provides a solid foundation for further investigation in clinical practice to determine its added value in shared decision making.
Original languageEnglish
Article number187
JournalCancers
Volume11
Issue number2
DOIs
Publication statusPublished - 1 Feb 2019

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